Vision

MilestoneMaker aims to revolutionize personalized learning by combining blockchain technology with AI-driven educational pathways. Our vision is to create a decentralized platform where learners can set their own goals, track their progress, and earn verifiable achievements, all while being guided by an intelligent AI agent.

Introduction

In this post, we will create an innovative learning platform (called MilestoneMaker) that blends the power of blockchain technology with artificial intelligence to offer customized educational experiences. We've crafted an AI agent that autonomously creates personalized learning paths tailored to each user's input. These learning paths are securely recorded on the blockchain, ensuring transparent and immutable tracking of every learner's progress.

One of the standout features is the AI agent's ability to autonomously manage all interactions with smart contracts.By automating complex blockchain processes, the AI agent significantly reduces the entry barriers for users who are new to decentralized applications (dApps). This user-centric approach makes the platform accessible and fosters the mass adoption of Web3 technologies, opening up a world of possibilities for a broader audience.

Key Features

• Personalized Learning Paths: The AI agent generates learning paths tailored to each user's needs and goals, while also managing interactions with smart contracts to ensure secure and efficient progress tracking.
• Blockchain-Based Progress Tracking: All learning milestones are tracked on the blockchain, providing a transparent and immutable record of each learner's achievements.
• NFT Minting for Achievements: Upon completing learning milestones, users can mint NFTs that serve as tangible proof of their skills and accomplishments.
• Interactive User Interface: Learners can input their goals, monitor their progress, and manage their educational journey through an intuitive and interactive interface. The integration of the Hive-Agent Kit enables the AI to comprehend complex learning requirements and decompose them into actionable milestones, creating a powerful synergy between human intent and machine intelligence in education.

Workflow

Firstly, the user connects to the application with their wallet (e.g., MetaMask). They can then type any topics they want to learn, such as 'I want to learn basic HTML' or 'I want to learn advanced Python in ten days,' etc. Based on this prompt, the AI Agent generates a learning path suitable for the user's requirements. The content is stored on IPFS, and the CID (hash value from IPFS) is stored on the blockchain by AI Agent.

Now, users can learn from the AI-generated content. This content provides the tasks they need to complete and includes references that users can access at any time. When users check the checkbox, their progress is updated on the blockchain by AI Agent. Once all tasks are completed, they need to pass a short quiz to verify their understanding.

If users correctly answer 80% of the quizzes, they will pass it and be able to mint an NFT as an achievement. Once the NFT is successfully minted, they can view it in the achievement tab.

High Level Architecture

In this architecture, we have four main components:

• dApp: A decentralized application that interacts with the backend server, smart contracts on the blockchain, and also stores data on IPFS.
• Backend Server: Responsible for managing the AI agent and interacting with the smart contract. We use the SwarmZero Kit to integrate the AI agent with OpenAI, but it is not limited to this; you can use other LLMs such as LLaMA 3, Phi 3, etc.
• Blockchain: The smart contract runs on the blockchain to store the status of the user's learning progress.
• IPFS: Used for storing user learning content.

Set Up and Implementation

Please checkout the GitHub for more details.
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